Wang Hanwen, Su Bingyi, Lu Lu, Jung Sehee, Qing Liwei, Xie Ziyang, Xu Xu
Edward P. Fitts Department of Industrial and Systems Engineering North, Carolina State University, Raleigh NC, 27695, USA.
Edward P. Fitts Department of Industrial and Systems Engineering North, Carolina State University, Raleigh NC, 27695, USA.
J Biomech. 2024 Mar;165:112027. doi: 10.1016/j.jbiomech.2024.112027. Epub 2024 Feb 28.
The assessment of gait performance using quantitative measures can yield crucial insights into an individual's health status. Recently, computer vision-based human pose estimation has emerged as a promising solution for markerless gait analysis, as it allows for the direct extraction of gait parameters from videos. This study aimed to compare the lower extremity kinematics and spatiotemporal gait parameters obtained from a single-camera-based markerless method with those acquired from a marker-based motion tracking system across a healthy population. Additionally, we investigated the impact of camera viewing angles and distances on the accuracy of the markerless method. Our findings demonstrated a robust correlation and agreement (R > 0.75, R > 0.7) between the markerless and marker-based methods for most spatiotemporal gait parameters. We also observed strong correlations (R > 0.8) between the two methods for hip flexion/extension, knee flexion/extension, hip abduction/adduction, and hip internal/external rotation. Statistical tests revealed significant effects of viewing angles and distances on the accuracy of the identified gait parameters. While the markerless method offers an alternative for general gait analysis, particularly when marker use is impractical, its accuracy for clinical applications remains insufficient and requires substantial improvement. Future investigations should explore the potential of the markerless system to measure gait parameters in pathological gaits.
使用定量测量方法评估步态表现可以为个人健康状况提供关键见解。最近，基于计算机视觉的人体姿态估计已成为无标记步态分析的一种有前景的解决方案，因为它允许从视频中直接提取步态参数。本研究旨在比较基于单摄像头的无标记方法与基于标记的运动跟踪系统在健康人群中获得的下肢运动学和时空步态参数。此外，我们研究了摄像头视角和距离对无标记方法准确性的影响。我们的研究结果表明，对于大多数时空步态参数，无标记方法和基于标记的方法之间存在很强的相关性和一致性（R > 0.75，R > 0.7）。我们还观察到两种方法在髋关节屈伸、膝关节屈伸、髋关节外展/内收和髋关节内/外旋转方面有很强的相关性（R > 0.8）。统计测试表明，视角和距离对所识别的步态参数的准确性有显著影响。虽然无标记方法为一般步态分析提供了一种替代方案，特别是在使用标记不切实际的情况下，但其在临床应用中的准确性仍然不足，需要大幅提高。未来的研究应探索无标记系统在测量病理步态中的步态参数方面的潜力。
